Evidence shows a growing disparity in the prevalence of modifiable risk factors and incidence of cardiovascular disease (C.D.) between upper and lower socioeconomic status (SES) individuals. Trends in knowledge about risk factors and risk reduction strategies parallel these findings. Research determining the differential association between level of C.D. knowledge and subsequent clinical health status has not been conducted. The purpose of this research is to elucidate the interrelationship by merging population-based, C.D. risk factor survey data with patient-level hospital data. The overall goal is to assess outcomes in the +/- association between level of C.D. knowledge and incidence and relative degree of morbidity among a cohort with and without major C.D. risk factors. The study population will be comprised of 2,560 adults, aged 21- 74 years, who took part in the final Stanford five-City (FCP cross- sectional survey in 1989/90. Analyses will be stratified according to SES (via years of formal education), controlling for age, gender, and ethnicity (Latino/Anglo). Sociodemographic, physiologic, and knowledge measurements are available on each participant. Morbidity estimates and clinical health status indicators are available via primary and secondary discharge diagnostic codes from public-use hospital discharge databases collected on all California hospital admissions for the entire study period. The FCP data will be merged with the hospital discharge data, matching on survey participant~s social security number which will be subsequently converted to a unique personal identifier. Baseline 1989/90 and 1991 through 1995 longitudinal outcomes will be assessed. There are three main aims, all of which have epidemiologic and C.D. health policy prevention implications: Aim 1: Characterize the distribution of hospitalized versus non- hospitalized SES sub-cohorts according to level of C.D. knowledge, physiologic risk factor prevalence, and clinical morbidity prevalence. Aim 2: Test the hypothesis that morbidity differences between hospitalized SES sub-cohorts will vary as a function of baseline level of C.D. knowledge and risk factor prevalence. Aim 3: Test the hypothesis that morbidity will rise among hospitalized lower SES sub-cohorts, resulting in widening health status disparities by the end of the study period. Parametric and nonparametric analytic methods will be used, including analysis of variance and covariance, and various regression techniques.